Zobrazeno 1 - 10
of 984
pro vyhledávání: '"Ono, Satoshi"'
Autor:
Ohta, Kazuhiro, Ono, Satoshi
Neural Radiance Field (NeRF), capable of synthesizing high-quality novel viewpoint images, suffers from issues like artifact occurrence due to its fixed sampling points during rendering. This study proposes a method that optimizes sampling points to
Externí odkaz:
http://arxiv.org/abs/2410.14958
Autor:
Tajima, Ayane, Ono, Satoshi
Publikováno v:
IEEE World Congress on Computational Intelligence (IEEE WCCI 2024), (2024)
Research has shown that deep neural networks (DNNs) have vulnerabilities that can lead to the misrecognition of Adversarial Examples (AEs) with specifically designed perturbations. Various adversarial attack methods have been proposed to detect vulne
Externí odkaz:
http://arxiv.org/abs/2407.02248
Autor:
Ono, Satoshi.
Publikováno v:
Online access via UMI.
Thesis (Ph. D.)--State University of New York at Binghamton, Thomas J. Watson School of Engineering and Applied Science, Department of Computer Science, 2009.
Includes bibliographical references.
Includes bibliographical references.
Externí odkaz:
http://proxy.binghamton.edu/login?url=http://wwwlib.umi.com/dissertations/fullcit/3368959
Autor:
Arai, Yuuki, Shitama, Hiroaki, Yamagishi, Masahito, Ono, Satoshi, Kashima, Akiko, Hiraizumi, Masahiro, Tsuda, Naoki, Katayama, Koushirou, Tanaka, Kouji, Koda, Yuzo, Kato, Sayuka, Sakata, Kei, Nureki, Osamu, Miyazaki, Hiroshi
Publikováno v:
In Bioorganic & Medicinal Chemistry 15 July 2024 109
Publikováno v:
In Gastroenterology Clinics of North America March 2024 53(1):25-38
Publikováno v:
2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Melbourne, Australia, 2021, pp. 3466-3471
This paper proposes an adversarial attack method to deep neural networks (DNNs) for monocular depth estimation, i.e., estimating the depth from a single image. Single image depth estimation has improved drastically in recent years due to the developm
Externí odkaz:
http://arxiv.org/abs/2101.10452
Autor:
Ishida, Shoma, Ono, Satoshi
Publikováno v:
Artif Life Robotics 26 (2021) 243-249
This paper proposes a black-box adversarial attack method to automatic speech recognition systems. Some studies have attempted to attack neural networks for speech recognition; however, these methods did not consider the robustness of generated adver
Externí odkaz:
http://arxiv.org/abs/2012.11138
Autor:
Kinoshita, Takahiro, Ono, Satoshi
Publikováno v:
International Workshop on Advanced Imaging Technology (IWAIT) 2021, Vol. 11766
Depth (disparity) estimation from 4D Light Field (LF) images has been a research topic for the last couple of years. Most studies have focused on depth estimation from static 4D LF images while not considering temporal information, i.e., LF videos. T
Externí odkaz:
http://arxiv.org/abs/2012.03021
Publikováno v:
IEEE Congress on Evolutionary Computation (CEC), (2019), 2136-2144
This paper proposes Evolutionary Multi-objective Optimization (EMO)-based Adversarial Example (AE) design method that performs under black-box setting. Previous gradient-based methods produce AEs by changing all pixels of a target image, while previo
Externí odkaz:
http://arxiv.org/abs/2001.05844
Akademický článek
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